Bottom Line:
It is found that, during G1/S transition in the cell cycle process, the regulatory networks are robustly constructed, and the robustness property is largely preserved with respect to small perturbations to the network.By using the unique process-based approach, the structure of this network is analyzed.It is shown that the network can be decomposed into a backbone motif which provides the main biological functions, and a remaining motif which makes the regulatory system more stable.

ABSTRACTBased on interactions among transcription factors, oncogenes, tumor suppressors and microRNAs, a Boolean model of cancer network regulated by miR-17-92 cluster is constructed, and the network is associated with the control of G1/S transition in the mammalian cell cycle. The robustness properties of this regulatory network are investigated by virtue of the Boolean network theory. It is found that, during G1/S transition in the cell cycle process, the regulatory networks are robustly constructed, and the robustness property is largely preserved with respect to small perturbations to the network. By using the unique process-based approach, the structure of this network is analyzed. It is shown that the network can be decomposed into a backbone motif which provides the main biological functions, and a remaining motif which makes the regulatory system more stable. The critical role of miR-17-92 in suppressing the G1/S cell cycle checkpoint and increasing the uncontrolled proliferation of the cancer cells by targeting a genetic network of interacting proteins is displayed with our model.

pone-0057009-g004: Perturbation of deleting interaction.The distribution of relative changes () under the perturbation of deleting 21 interaction arrows from the MGSTR network and random networks. The majority of values are small, which indicates that most perturbations will not alter the size of the biggest attractor significantly.

Mentions:
The size of basin of attractors (B) in a system is a vital quantity in terms of understanding network behavior and may relate to other network properties such as stability. Therefore, the relative change in B for the biggest attractor can be served as a measurement in our robustness test. The MGSTR network and the random networks are perturbed by deleting an interaction arrow (Fig. 4), adding a green or blue arrow between nodes that are -linked (Fig. 5), or switching the interaction of a single arrow from inhibition to activation and vice versa (Fig. 6) [8]. It is shown that most perturbations will not alter the size of the biggest attractor significantly ( is small)in MGSTR network, which suggests our MGSTR network has high homeostatic stability[8]. Such high homeostatic stability is not well maintained in the ensemble of random networks with the same size (Fig. 4–6). High robustness of the MGSTR network may be attributed to the structure and interactions within the regulatory system.

pone-0057009-g004: Perturbation of deleting interaction.The distribution of relative changes () under the perturbation of deleting 21 interaction arrows from the MGSTR network and random networks. The majority of values are small, which indicates that most perturbations will not alter the size of the biggest attractor significantly.

Mentions:
The size of basin of attractors (B) in a system is a vital quantity in terms of understanding network behavior and may relate to other network properties such as stability. Therefore, the relative change in B for the biggest attractor can be served as a measurement in our robustness test. The MGSTR network and the random networks are perturbed by deleting an interaction arrow (Fig. 4), adding a green or blue arrow between nodes that are -linked (Fig. 5), or switching the interaction of a single arrow from inhibition to activation and vice versa (Fig. 6) [8]. It is shown that most perturbations will not alter the size of the biggest attractor significantly ( is small)in MGSTR network, which suggests our MGSTR network has high homeostatic stability[8]. Such high homeostatic stability is not well maintained in the ensemble of random networks with the same size (Fig. 4–6). High robustness of the MGSTR network may be attributed to the structure and interactions within the regulatory system.

Bottom Line:
It is found that, during G1/S transition in the cell cycle process, the regulatory networks are robustly constructed, and the robustness property is largely preserved with respect to small perturbations to the network.By using the unique process-based approach, the structure of this network is analyzed.It is shown that the network can be decomposed into a backbone motif which provides the main biological functions, and a remaining motif which makes the regulatory system more stable.

ABSTRACTBased on interactions among transcription factors, oncogenes, tumor suppressors and microRNAs, a Boolean model of cancer network regulated by miR-17-92 cluster is constructed, and the network is associated with the control of G1/S transition in the mammalian cell cycle. The robustness properties of this regulatory network are investigated by virtue of the Boolean network theory. It is found that, during G1/S transition in the cell cycle process, the regulatory networks are robustly constructed, and the robustness property is largely preserved with respect to small perturbations to the network. By using the unique process-based approach, the structure of this network is analyzed. It is shown that the network can be decomposed into a backbone motif which provides the main biological functions, and a remaining motif which makes the regulatory system more stable. The critical role of miR-17-92 in suppressing the G1/S cell cycle checkpoint and increasing the uncontrolled proliferation of the cancer cells by targeting a genetic network of interacting proteins is displayed with our model.